Device and method for compensating for nonlinearity of power amplifier

ABSTRACT

A device configured to perform wireless communication includes: a pre-distortion circuit configured to generate a pre-distorted input signal by performing pre-distortion on an input signal based on a parameter set comprising a plurality of coefficients; a power amplifier configured to generate an output signal by amplifying an RF signal based on the pre-distorted input signal; and a parameter obtaining circuit configured to obtain second memory polynomial modeling information corresponding to an operating frequency band based on first memory polynomial modeling information corresponding to each of a plurality of frequency sections and obtain a parameter set according to an indirect learning structure by using the second memory polynomial modeling information.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of Korean Patent Application No.10-2019-0083441, filed on Jul. 10, 2019, in the Korean IntellectualProperty Office, the disclosure of which is incorporated herein byreference in its entirety.

TECHNICAL FIELD

This disclosure relates generally to a device and method forcompensating for nonlinearity of a power amplifier, such as a poweramplifier of a wireless communication device.

DISCUSSION OF THE RELATED ART

Devices for wireless communication may include transmitters providingradio frequency (RF) signals that are output to antennas. A transmittermay include components for generating the RF signals from basebandsignals, such as a mixer for upconverting the baseband signals to RFsignals, one or more filters, and an RF power amplifier. When thebaseband signals are processed by the components of the transmitter, theRF signals may become distorted due to characteristics of thecomponents. For example, the power amplifier in particular may exhibitnonlinear gain and phase as a function of input signal power, and thisnonlinearity may degrade communication quality by distorting the RFoutput signals. In the case of digital baseband signals, distortion dueto operation in a gain compression region of the power amplifier maylead to excessive bit errors particularly for bits represented byrelatively higher power signals. To reduce distortion, a digitalpre-distortion or RF pre-distortion technique may be used to pre-distortthe input RF signal to the power amplifier in a complementary manner tothe power amplifier characteristics. However, at higher RF frequenciesand in the presence of a plurality of antenna elements of an antennaarray (where mutual coupling may affect the power amplifiers), the RFsignal distortion may be exacerbated and may be more difficult tocompensate using a pre-distortion method.

SUMMARY

Embodiments of the inventive concept provides a device and method forcompensating for nonlinearity of a power amplifier, and moreparticularly, a device and method for adaptively performingpre-distortion on various frequency bands while reducing a storage spaceof a memory used for the pre-distortion.

According to an aspect of the inventive concept, there is provided adevice configured to perform wireless communication including: apre-distortion circuit configured to generate a pre-distorted inputsignal by performing pre-distortion on an input signal based on aparameter set including a plurality of coefficients; a power amplifierconfigured to generate an output signal by amplifying an RF signal basedon the pre-distorted input signal; and a parameter obtaining circuitconfigured to obtain second memory polynomial modeling informationcorresponding to an operating frequency band based on first memorypolynomial modeling information corresponding to each of a plurality offrequency sections and obtain a parameter set according to an indirectlearning structure by using the second memory polynomial modelinginformation.

According to another aspect of the inventive concept, there is provideda method of processing a signal of a device, the method including:determining at least one frequency section including at least a portionof an operating frequency band of the device among a plurality offrequency sections that are divided from an entire frequency band overwhich the device is configured to operate; obtaining an auto-correlationvector corresponding to the operating frequency band and across-correlation matrix corresponding to the operating frequency band,based on a frequency section information corresponding to the determinedat least one frequency section; and generating an output signal byperforming pre-distortion on an input signal by using a coefficientmatrix that is obtained based on the auto-correlation matrixcorresponding to the operating frequency band and the cross-correlationvector corresponding to the operating frequency band.

According to another aspect of the inventive concept, there is provideda device configured to perform wireless communication, the deviceincluding: a memory configured to store a plurality of pieces offrequency section information for a plurality of frequency sections andinstructions for operation of the device; a processor configured toperform pre-distortion on an input signal in a given frequency band byexecuting at least one instruction among the instructions stored in thememory and generate the pre-distorted input signal; and a poweramplifier configured to generate an output signal by amplifying thepre-distorted input signal, wherein the processor is configured todetermine at least one frequency section including at least a portion ofthe given frequency band among the plurality of frequency sections andperform a pre-distortion calculation on the input signal by using acoefficient matrix obtained by using frequency section informationcorresponding to the determined at least one frequency section among theplurality of pieces of frequency section information.

According to another aspect of the inventive concept, there is provideda method of performing a pre-distortion calculation on an input signalof a frequency band spanning over a first frequency section and a secondfrequency section, performed by a device, the method including:obtaining a first auto-correlation matrix corresponding to the firstfrequency section, a second auto-correlation matrix corresponding to thesecond frequency section, and an auto-correlation matrix correspondingto the frequency band based on a center frequency of the frequency band;obtaining a first cross-correlation vector corresponding to the firstfrequency section, a second cross-correlation vector corresponding tothe second frequency section, and a cross-correlation vectorcorresponding to the frequency band based on the center frequency of thefrequency band; and performing pre-distortion on the input signal byusing the coefficient matrix obtained based on the obtainedauto-correlation matrix and the obtained cross-correlation vector.

According to another aspect of the inventive concept, there is provideda device configured to perform wireless communication, the deviceincluding: a memory configured to store a plurality of pieces offrequency section information for each of a plurality of frequencysections divided in an entire frequency band over which the device isconfigured to operate; a processor configured to generate apre-distorted input signal by performing pre-distortion on an inputsignal in a given frequency band; and an amplifier configured togenerate an output signal based on the pre-distorted input signalprovided by the processor, wherein the processor is configured to, whenthe given frequency band spans over a first frequency section and asecond frequency section among the plurality of frequency sections,perform the pre-distortion on the input signal by using a coefficientmatrix obtained based on a first frequency section informationcorresponding to the first frequency section and a second frequencysection information corresponding to the second frequency section, andwhen the given frequency band spans over a third frequency section and afourth frequency section among the plurality of frequency sections,perform the pre-distortion on the input signal by using a coefficientmatrix obtained based on third frequency section informationcorresponding to the third frequency section and fourth frequencysection information corresponding to the fourth frequency section.

According to another aspect of the inventive concept, there is provideda device configured to perform wireless communication, the deviceincluding: a memory configured to store a plurality of pieces of memorypolynomial modeling information corresponding to each of a plurality offrequency sections divided from an entire frequency band over which thedevice is configured to operate; and a processor configured to obtainsecond memory polynomial modeling information corresponding to anoperating frequency band by using at least one piece of first memorypolynomial modeling information corresponding to at least one firstfrequency section including at least a portion of the operatingfrequency band of the plurality of frequency sections among theplurality of pieces of memory polynomial modeling information, andgenerate a pre-distorted input signal by performing pre-distortion on aninput signal by using a parameter set obtained by using the secondmemory polynomial modeling information.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the inventive concept will be more clearly understoodfrom the following detailed description taken in conjunction with theaccompanying drawings in which:

FIG. 1 illustrates a device according to an example embodiment of theinventive concept;

FIG. 2 illustrates example input-output characteristics of a poweramplifier;

FIG. 3 illustrates a device according to an example embodiment of theinventive concept;

FIG. 4 illustrates a plurality of frequency sections included in theentire frequency band, according to an example embodiment of inventiveconcept;

FIG. 5 illustrates an entire frequency band and a given frequency band,according to an example embodiment of the inventive concept;

FIG. 6 is a diagram of a parameter obtaining circuit according to anexample embodiment of the inventive concept;

FIG. 7 illustrates a frequency section information according to anexample embodiment of the inventive concept;

FIG. 8 is a flowchart of a signal processing method of a device,according to an example embodiment of the inventive concept;

FIG. 9 is a flowchart of a signal processing method according to anexample embodiment of the inventive concept;

FIG. 10 is a flowchart of a signal processing method according to anexample embodiment of the inventive concept;

FIG. 11 is a flowchart of a signal processing method according to anexample embodiment of the inventive concept;

FIG. 12 is a flowchart of a signal processing method according to anexample embodiment of the inventive concept;

FIG. 13 is a parameter obtaining circuit according to an exampleembodiment of the inventive concept;

FIG. 14 is a parameter obtaining circuit according to an exampleembodiment of the inventive concept;

FIG. 15 illustrates an entire frequency band and a plurality offrequency sections, according to an example embodiment of inventiveconcept;

FIG. 16 illustrates an entire frequency band and a plurality offrequency sections, according to an example embodiment of inventiveconcept; and

FIG. 17 illustrates a communication device according to an exampleembodiment of the inventive concept.

DETAILED DESCRIPTION OF EMBODIMENTS

Hereinafter, embodiments of the inventive concept are described indetail with reference to the accompanying drawings.

FIG. 1 illustrates a device 10 according to an example embodiment of theinventive concept. The device 10 may comprise a pre-distortion circuit100, a transmitter 200, and a parameter obtaining circuit 300. Thedevice 10 may be a communication device, typically a wirelesscommunication device. The device 10 may be a base station or userequipment included in a wireless communication system. The wirelesscommunication system may be, as non-limiting examples, a wirelesscommunication system using a cellular network such as a 5th generation(5G) wireless system, a long term evolution (LTE) system, anLTE-advanced system, a code division multiple access (CDMA) system, aglobal system for mobile communications (GSM) system, or any otherwireless communication system such as wireless local area network(WLAN), WiFi, and Bluetooth. The base station may be referred to as aNode B, an evolved-Node B (eNB), a sector, a site, a base transceiversystem (BTS), an access point (AP), a relay node, and a remote radiohead (RRH), a radio unit (RU), a small cell, etc. The user equipment maybe referred to as terminal equipment, a mobile station (MS), a mobileterminal (MT), a user terminal (UT), a subscriber station (SS), awireless device, a handheld device, etc. The device 10 may furtherinclude various components in addition to the components illustrated inFIG. 1.

The transmitter 200 may process a baseband pre-distorted signal PDS andgenerate an RF output signal OS. For example, the transmitter 200 mayinclude an upconverter 202 for upconverting the pre-distorted signal PDSto an input RF signal RFin, and a power amplifier 204 that amplifies thesignal RFin to generate the output signal OS. Herein, the input RFsignal RFin may be referred to as a pre-distorted RF signal, and may bereferred to as an RF signal that is based on the pre-distorted signalPDS. The transmitter 200 and/or the pre-distortion circuit 100 may alsoinclude various filters (not shown) such as a low pass filter to smoothout inter-symbol transitions.

In general, linear characteristics may be required for outputcharacteristics of the power amplifier 204, but the power amplifier 204may have nonlinear characteristics due to characteristics of the poweramplifier 204 itself or various peripheral factors. In other words, asillustrated in FIG. 2, the output characteristics of the power amplifier204 may exhibit nonlinear characteristics.

FIG. 2 illustrates example input-output characteristics of the poweramplifier 204.

A solid line may represent characteristics of a desired gain for thepower amplifier 204. As illustrated in FIG. 2, the characteristic of thedesired gain may represent characteristics in which an input voltage isproportional to an output voltage.

However, an actual gain of the power amplifier 204 may exhibit the samecharacteristics as a dashed line in FIG. 2. In other words, the actualgain characteristics of the power amplifier 204 may represent thenonlinear characteristics in which the input voltage and the outputvoltage are not proportional to each other in a particular region.

Referring further to FIG. 1, the pre-distortion may be used tocompensate for the nonlinearity of the power amplifier 204. Thepre-distortion may be referred to as a technique of pre-distorting theinput signal IS according to characteristics complementary to thenonlinearity of the power amplifier 204.

For example, the pre-distortion circuit 100 may generate a basebandpre-distorted signal PDS by performing the pre-distortion on the inputsignal IS. The pre-distortion circuit 100 may provide the pre-distortedsignal PDS to the transmitter 200. The power amplifier 204 may generatethe output signal OS by amplifying the pre-distorted RF signal RFin. Asthe pre-distortion circuit 100 performs the pre-distortion on the inputsignal IS, the nonlinearity of the power amplifier 204 may becompensated for. In an embodiment, the pre-distortion circuit 100 mayperform a digital pre-distortion on the input signal IS.

In an embodiment, the pre-distortion circuit 100 may perform thepre-distortion on the input signal IS based on a parameter set PS. Theparameter set PS may be provided by the parameter obtaining circuit 300.The parameter set PS may include a plurality of coefficients used forthe pre-distortion.

Here, the input signal IS and the pre-distorted signal PDS may bedigital signals such as a phase shift keyed (PSK) signal, a quadratureamplitude modulation signal (QAM signal), and so forth. The outputsignal OS may be referred to as a modulated digital signal.

The pre-distortion circuit 100 may be modeled by using a polynomial asshown in Formula 1 below. Here, the polynomial modeling may be referredto as a memory polynomial modeling. In Formula 1, x (n) represents asample of the input signal IS, z (n) represents a sample of thepre-distorted signal PDS, a_(q) represents a coefficient used for thepre-distortion, and Q represents a nonlinear order.

$\begin{matrix}{{z(n)} = {\sum\limits_{q = 0}^{Q - 1}{a_{q}{x(n)}{{x(n)}}^{q}}}} & \left\lbrack {{Formul}\; a\mspace{14mu} 1} \right\rbrack\end{matrix}$

The pre-distortion circuit 100 may be implemented in various forms.According to an embodiment, the pre-distortion circuit 100 may beimplemented by hardware or software. When the pre-distortion circuit 100is implemented by hardware, the pre-distortion circuit 100 may includecircuits for performing the pre-distortion on the input signal IS. Whenthe pre-distortion circuit 100 is implemented by software, thepre-distortion may be performed by executing programs and/orinstructions loaded into the memory 400, by a processor (500 in FIG. 3)or any processor in the device 10. In other examples, the pre-distortioncircuit 100 may be implemented by a combination of software and hardwaresuch as firmware.

The parameter obtaining circuit 300 may obtain the parameter set PSbased on the pre-distorted signal PDS and output signal OS and mayprovide the generated parameter set PS to the pre-distortion circuit100.

In an embodiment, the parameter obtaining circuit 300 may obtain theparameter set PS including a plurality of coefficients based on anindirect learning structure. The indirect learning structure mayrepresent a learning structure in which a difference between anintermediate signal obtained from the output signal OS and thepre-distorted signal PDS is minimized, instead of a difference betweenthe input signal IS and the output signal OS. When y (n) represents asample of the output signal OS, w (n) represents a sample of theintermediate signal, a_(kq) represents a coefficient, Q represents thenonlinear order, and K represents a memory depth, the intermediatesignal may be a signal obtained by using a polynomial formula such asFormula 2 below.

$\begin{matrix}{{w(n)} = {\sum\limits_{K = 0}^{K - 1}{\sum\limits_{q = 0}^{Q - 1}{a_{kq}{y\left( {n - k} \right)}{{y\left( {n - k} \right)}}^{q}}}}} & \left\lbrack {{Formul}\; a\mspace{14mu} 2} \right\rbrack\end{matrix}$

The parameter obtaining circuit 300 may obtain the parameter set PS thatreduces the difference between the intermediate signal obtained asdescribed above based on the output signal OS and the pre-distortedsignal PDS, by using the indirect learning structure. In an embodiment,the parameter obtaining circuit 300 may obtain the parameter set PS thatminimizes a mean squared error (MSE) between the intermediate signal andthe pre-distorted signal PDS. When z (n) represents a sample of thepre-distorted signal PDS, w (n) represents a sample of the intermediatesignal, and e (n) represents a sample of an error signal, the MSE may beobtained by using Formula 3 below.MSE=E[e ²(n)]=E[|z(n)−w(n)|²]  [Formula 3]

Factors that minimize the MSE may be obtained by using the Wienerfilter. In other words, the parameter obtaining circuit 300 may obtainthe parameter sets PS including the coefficients a_(kq) that minimizethe MSE by applying the Wiener filter. In this case, as the Wienerfilter is applied, a procedure of obtaining coefficients that minimizethe MSE may involve solving a matrix equation in Formula 4 below. InFormula 4, y (n) represents a sample of the output signal OS, z (n)represents a sample of the pre-distorted signal PDS, Q represents thenonlinear order, and K represents the memory depth.Ax=b(A=E[Y(n)Y ^(H)(n)],x=[a ₀₀ a ₀₁ a ₀₂ . . . a _(K−1Q−1)]^(T) ,b=E[Y(n)z^(H)(n)],Y(n)=[y(n),y(n)|y(n)|, . . . ,y(n)|y(n)|^(Q−1) ,y(n−1), . . .,y(n−K+1)|y(n−K+1)|^(Q−1)]^(T)  [Formula 4]

In Formula 4, a matrix with T as a superscript denotes a transposedmatrix. A matrix with H as a superscript is a Hermitian matrix, which isa matrix obtained by transposing after conjugates are applied to allelements of the matrix. In other words, the matrix with H as asuperscript is a conjugate transposed matrix. E [ ] represents anexpectation of a value included therein. Y (n) may be a KQ×1 matrix inwhich an element corresponding to an i*j^(th) row and a first column hasa value as shown in Formula 5 below.Y(n)[i*j,1]=y(n−i+1)|y(n−i+1)|y(n−i+1)|^(j−1)  [Formula 5]

Here, x may be a KQ*1 matrix in which an element corresponding to thei*j^(th) row and the first column has a value in Formula 6 below.x[i*j,1]=a _((i−1)(j−1))  [Formula 6]

As a result, the matrix A used in a method of applying the Wiener filtermay be a KQ×KQ matrix, and the matrix b may be a KQ×1 matrix. In otherwords, the matrix b may be a vector having KQ elements. Hereinafter, forconvenience of description, in the method of applying the Wiener filterto Formula 4, the matrix A used in the equivalent matrix equation may bereferred to as an auto-correlation matrix, and the matrix b may bereferred to as a cross-correlation vector. In addition, the matrix xincluding the coefficients may be referred to as a coefficient matrix.In other words, obtaining the parameter set PS may include obtaining thecoefficient matrix b by obtaining a solution of the matrix equation ofFormula 4. In this manner, the auto-correlation matrix and thecross-correlation vector required for obtaining the coefficient matrixmay be referred to as “memory polynomial modeling information”(interchangeably, just “polynomial modeling information”), which may beinformation based on signal measurements and subsequent calculationsusing the measurement results, which information may be stored in thememory 400 within the device 10.

With regard to frequencies of operation, the operating frequency bandmay vary depending on a type or set-up of the device 10. For example, acenter frequency and a frequency bandwidth of the operating frequencyband that are set for the device 10's operation may vary. When theoperating frequency band is changed, the memory polynomial modelinginformation required for obtaining the coefficient matrix x from theparameter obtaining circuit 300 may vary according to characteristics ofthe power amplifier 204. In other words, without implementation of theinventive concept taught herein, the device 10 may need to store thememory polynomial modeling information for each of the possiblefrequency bands to provide highly reliable pre-distortion. However,storing all of the memory polynomial modeling information for each ofthe possible frequency bands may cause a requirement of a large memorystorage space. On the other hand, with embodiments described herein, amethod of performing the pre-distortion for the various frequency bandsmay be implemented by using a smaller memory storage space.

The parameter obtaining circuit 300 according to an example embodimentof the inventive concept may use frequency section information FSI for aplurality of frequency bands that are pre-divided in an entire frequencyband over which the device 10 is configured to operate, for obtainingthe memory polynomial modeling information corresponding to the given(operating) frequency band. The frequency section information FSI may bestored in the memory 400. Herein, the term ‘given frequency band’ may bea term to represent the operating frequency band that is currentlyallocated for an operation of the device 10. A “given frequency band”may be interchangeably referred to as a sub-band or a channel of theentire frequency band. There may be many given frequency bands possiblewithin an entire frequency band of operation of the device 10.

To this end, the device 10 may divide the entire frequency band into aplurality of frequency sections, and after the polynomial modelinginformation corresponding to each of the plurality of frequency sectionsis obtained, may generate the polynomial modeling informationcorresponding to each of the plurality of frequency sections and thefrequency section information FSI including the center frequency of eachof the plurality of frequency sections, and the memory 400 may generatethe frequency section information FSI. The plurality of frequencysections are described in more detail with reference to FIGS. 4, 15, and16, and the frequency section information FSI is described in detailwith reference to FIG. 7. A number “N” of frequency sections may besmaller than a number “M” of permissible given frequency bands withinthe entire frequency band over which the device 10 is configured tooperate. Instead of separately measuring and calculating polynomialmodeling information for each given frequency band, this information maybe obtained through calculation based on the polynomial modelinginformation for one or more of the frequency sections that overlap thegiven frequency band. Thus, by obtaining the polynomial modelinginformation for the smaller number N of frequency sections, the amountof measurements and computations performed beforehand to cover allpermissible given frequency bands, and/or the amount of memory spaceused to store the information, may be reduced.

According to an embodiment, the parameter obtaining circuit 300 maydetermine at least one frequency section including at least a portion ofa given frequency band among the plurality of frequency sections and mayobtain the polynomial modeling information corresponding to thefrequency band that is provided based on the frequency sectioninformation FSI corresponding to the determined at least one frequencysection.

For example, the parameter obtaining circuit 300 may obtain theauto-correlation matrix corresponding to the determined at least onefrequency section, the center frequency corresponding to the determinedat least one frequency section, and the auto-correlation matrixcorresponding to the frequency band that is given based on the centerfrequency of the given frequency band. In addition, the parameterobtaining circuit 300 may obtain the cross-correlation vectorcorresponding to the determined at least one frequency section, thecenter frequency corresponding to the determined at least one frequencysection, and the cross-correlation vector corresponding to the frequencyband that is given based on the center frequency of the given frequencyband. The parameter obtaining circuit 300 may obtain the coefficientmatrix based on the obtained auto-correlation matrix and the obtainedcross-correlation vector and may output the coefficient matrix orcoefficients included in the coefficient matrix as the parameter set PS.For example, the parameter obtaining circuit 300 may obtain thecoefficient matrix by performing a calculation of multiplying thecross-correlation vector by an inverse matrix of the obtainedauto-correlation matrix. Alternatively, in an embodiment, the parameterobtaining circuit 300 may obtain the coefficient matrix by performing aniterative approximation calculation using the obtained auto-correlationmatrix and the obtained cross-correlation vector, and in this case, anembodiment in which the parameter obtaining circuit 300 uses a conjugategradient method may be also applicable.

A method of obtaining the polynomial modeling information correspondingto the given frequency band based on the frequency section informationFSI about the plurality of frequency sections, for example, a method ofobtaining the auto-correlation matrix and the cross-correlation vectorcorresponding to the given frequency band by using the parameterobtaining circuit 300 is described in detail with reference to thefollowing drawings.

The parameter obtaining circuit 300 may be implemented in various forms,and according to an embodiment, the parameter obtaining circuit 300 maybe implemented by hardware or software. When the parameter obtainingcircuit 300 is implemented by hardware, the parameter obtaining circuit300 may include circuits for generating the parameter set PS based onthe output signal OS and the pre-distorted signal PDS. In addition, forexample, when the parameter obtaining circuit 300 is implemented bysoftware, as illustrated in FIG. 2, the parameter set PS may begenerated by executing programs and/or instructions loaded into thememory 400 by using the processor (500 in FIG. 3) or any processor inthe device 10. However, the embodiment is not limited thereto, and theparameter obtaining circuit 300 may be implemented by a combination ofsoftware and hardware, such firmware.

The memory 400 may be a storage area for storing data and may store, forexample, an operating system (OS), various programs, and various data.The memory 400 may include at least one of a volatile memory and anon-volatile memory. The non-volatile memory may include read-onlymemory (ROM), programmable ROM (PROM), electrically programmable ROM(EPROM), electrically erasable PROM (EEPROM), a flash memory,phase-change random-access memory (RAM) (PRAM), magnetic RAM (MRAM),resistive RAM (RRAM), ferroelectric RAM (FRAM), etc. The volatile memorymay include dynamic RAM (DRAM), static RAM (SRAM), synchronous DRAM(SDRAM), phase-change RAM (PRAM), magnetic RAM (MRAM), resistive RAM(RRAM), ferroelectric RAM (FeRAM), etc. In addition, in an embodiment,the memory 400 may include at least one of a hard disk drive (HDD), asolid state drive (SSD), a compact flash (CF) memory, a secure digital(SD) memory, a micro secure digital Secure digital), memory an extremedigital (xD) memory, or a memory stick. In an embodiment, the memory 400may semi-permanently or temporarily store programs and a plurality ofinstructions that are executed by the processor (500 in FIG. 3). Inaddition, the memory 400 may store various information or data used forcalculations or operations of the processor (500 in FIG. 3).

According to the device 10 according to an example embodiment of theinventive concept, as the parameter obtaining circuit 300 obtains thememory polynomial modeling information such as the auto-correlationmatrix or cross-correlation vector used for obtaining the coefficientmatrix based on the frequency section information FSI about theplurality of frequency sections, the amount of data to be stored by thememory 400 may be reduced. In other words, the storage space of thememory 400 used or required to perform the pre-distortion in the device10 may be reduced.

In addition, since the device 10 according to an example embodiment ofthe inventive concept is adaptively capable of performing thepre-distortion in various given frequency bands given over a widefrequency band by using only a small amount of storage space in thememory 400, the reliability of the wireless communication of the device10 may also be improved.

FIG. 3 illustrates a device 20 according to an example embodiment of theinventive concept. In particular, FIG. 3 is a diagram of animplementation example of the pre-distortion circuit 100, thetransmitter 200, the parameter obtaining circuit 300, and the memory400, which have been illustrated in FIG. 1. Redundant descriptions ofthe pre-distortion circuit 100, the transmitter 200, the parameterobtaining circuit 300, and the memory 400 in FIG. 3 that have beenalready given with reference to FIG. 1, are omitted.

The device 20 may include the transmitter 200, the memory 400, and theprocessor 500, and the processor 500 may include the pre-distortioncircuit 100 and the parameter obtaining circuit 300.

The processor 500 may control the entire operation of the device 10, andfor example, the processor 500 may be a central processing unit (CPU).The processor 500 may include only a single processor core oralternatively a plurality of processor cores (“multi-core”). Theprocessor 500 may process or execute programs and/or data stored in thememory 400. In an embodiment, the processor 500 may control variousfunctions or perform various calculations of the device 20 by executingprograms stored in the memory 400.

The processor 500 according to an example embodiment of the inventiveconcept may generate the pre-distorted signal PDS by performing thepre-distortion on the input signal IS. In an embodiment, the processor500 may obtain the memory polynomial modeling information correspondingto the given frequency band based on frequency section information FSIof the plurality of sections stored in the memory 400, obtain theparameter set PS based on the obtained polynomial modeling information,and perform the pre-distortion on the input signal IS based on theobtained parameter set PS.

With the device 20 according to an example embodiment of the inventiveconcept, since the processor 500 obtains the memory polynomial modelinginformation such as the auto-correlation matrix or cross-correlationvector used for obtaining the coefficient matrix based on the frequencysection information FSI about the plurality of frequency sections, theamount of data to be stored by the memory 400 may be reduced. In otherwords, the storage space of the memory 400 used or required to performthe pre-distortion in the device 20 may be reduced.

In addition, since the device 20 is adaptively capable of performing thepre-distortion in various given frequency bands over a wide frequencyband by using only a small amount of storage space in the memory 400,the reliability of the wireless communication of the device 20 may alsobe improved.

FIG. 4 illustrates first through fifth frequency sections FS_1 throughFS_5 included in the entire frequency band according to an exampleembodiment of the inventive concept. FIG. 4 is described with referenceto FIG. 1.

The device 10 may operate in a particular frequency band according to atype of the device 10 or a set-up applied thereto. FIG. 4 illustratesthe entire frequency band including all frequencies which the frequencyband may provide. For example, the entire frequency band may include afrequency band between a first frequency f_1 and a sixth frequency f_6.

To obtain polynomial modeling information, the device 10 may divide theentire frequency band into a plurality of frequency sections (FS_1,FS_2, FS_3, FS_4, and FS_5). The number of frequency sections andrespective frequency widths of the frequency sections are merelyexemplary for convenience of description and are not limited to thoseillustrated in FIG. 4. For example, the first frequency section FS_1 mayrepresent a frequency section between the first frequency f_1 and thesecond frequency f_2, and the center frequency of the first frequencysection FS_1 may be a first center frequency fc_1. Similarly, the secondfrequency section FS_2 may represent a frequency section between thesecond frequency f_2 and a third frequency f_3, and a center frequencyof the second frequency section FS_2 may be a second center frequencyfc_2. In the same manner, the third frequency section FS_3, the fourthfrequency section FS_4, and the fifth frequency section FS_5 may beunderstood.

In an embodiment, the first through fifth frequency sections FS_1through FS_5 may have the same frequency width. However, the embodimentis not limited thereto, and the first through fifth frequency sectionsFS_1 through FS_5 may have different frequency widths from each other.For example, a frequency section near the center of the entire frequencyband may have a narrower frequency width than a frequency sectionlocated near edges of the entire frequency band.

In an embodiment, the device 10 may obtain the memory polynomialmodeling information for each of the plurality of frequency sections(FS_1, FS_2, FS_3, FS_4, and FS_5), and the memory 400 in the device 10may store the memory polynomial modeling information obtained for eachof the plurality of frequency sections (FS_1, FS_2, FS_3, FS_4, andFS_5) and center frequencies of each of the plurality of frequencysections (FS_1, FS_2, FS_3, FS_4, and FS_5) as the frequency sectioninformation FSI. The frequency section information FSI is described inmore detail with reference to FIG. 7.

FIG. 5 illustrates the entire frequency band and a given frequency band,according to an example embodiment of the inventive concept. Inparticular, FIG. 5 illustrates a case in which the given frequency bandis a specific band within the entire frequency band divided asillustrated in FIG. 4. FIG. 5 is described below with reference to FIG.1.

The device 10 may operate in a particular frequency band according tovarious factors such as the type of the device 10 or the set-up thereof,and the particular frequency band may be referred to as the givenfrequency band. The given frequency band may have a center frequency fc.

FIG. 5 illustrates a case in which the given frequency band spans overthe third and fourth frequency section FS_3 and FS_4, but the embodimentis merely illustrative and is not limited thereto. For example, thegiven frequency band may span over at least one other frequency section.

In an embodiment, the parameter obtaining circuit 300 in the device 10may determine at least one frequency band including at least a portionof the given frequency band among the plurality of frequency sections(FS_1, FS_2, FS_3, FS_4, and FS_5). For example, the parameter obtainingcircuit 300 may determine that the third frequency section FS_3 and thefourth frequency section FS_4 include at least a portion of the givenfrequency band.

In an embodiment, the parameter obtaining circuit 300 may obtain thememory polynomial modeling information corresponding to the givenfrequency band based on the memory polynomial modeling informationcorresponding to the determined at least one frequency section. Forexample, the parameter obtaining circuit 300 may obtain the memorypolynomial modeling information corresponding to the given frequencyband, based on the memory polynomial modeling information correspondingto the third frequency section FS_3 and the memory polynomial modelinginformation corresponding to the fourth frequency section FS_4. Each ofthe memory polynomial modeling information may include anauto-correlation matrix and a cross-correlation vector that are used ina matrix equation for minimizing a difference between an intermediatesignal based on the output signal OS and the pre-distorted signal PDSaccording to an application of the Wiener filter. For example, each ofthe pieces of the memory polynomial modeling information may include theauto-correlation matrix A and the cross-correlation vector b in Formula4.

A method in which the parameter obtaining circuit 300 obtains the memorypolynomial modeling information corresponding to the given frequencyband is described in more detail with reference to FIG. 6.

FIG. 6 is a diagram of the parameter obtaining circuit 300 according toan example embodiment of the inventive concept. The parameter obtainingcircuit 300 may correspond to the parameter obtaining circuit 300 inFIGS. 1 and 3. FIG. 6 is described with reference to FIGS. 1 and 5together.

The parameter obtaining circuit 300 may include an auto-correlationmatrix obtaining circuit 310, a cross-correlation vector obtainingcircuit 320, and a coefficient matrix obtaining circuit 330.

The auto-correlation matrix obtaining circuit 310 may obtain anauto-correlation matrix ACM corresponding to the given frequency bandbased on the frequency section information FSI for the plurality offrequency section and provide the auto-correlation matrix ACM to thecoefficient matrix obtaining circuit 330.

The cross-correlation vector obtaining circuit 320 may obtain across-correlation vector CCV corresponding to the given frequency bandbased on frequency section information FSI for the plurality offrequency sections and provide the cross-correlation vector CCV to thecoefficient matrix obtaining circuit 330.

The coefficient matrix obtaining circuit 330 may obtain a coefficientmatrix CM corresponding to the given frequency band, based on theauto-correlation matrix ACM corresponding to the given frequency bandand the cross-correlation vector CCV corresponding to the givenfrequency band. For example, the coefficient matrix obtaining circuit330 may obtain the coefficient matrix CM by performing a calculation ofmultiplying the cross-correlation vector CCV by an inverse matrix of theauto-correlation matrix ACM. The coefficient matrix obtaining circuit330 may output the coefficient matrix CM as the parameter set PS.

FIG. 7 illustrates the frequency section information FSI according to anexample embodiment of the inventive concept. FIG. 7 is described withreference to FIGS. 1 and 5 together.

The frequency section information FSI may include first through Nthpieces of frequency section information FSI_1 through FSI N (N is anatural number of two or more) corresponding to each of the plurality offrequency sections. For example, when the entire frequency band isdivided into N frequency sections, the frequency section information FSImay include frequency section information corresponding to each of the Nfrequency sections.

The first frequency section information FSI_1 is described as arepresentative of the first through Nth pieces of frequency sectioninformation FSI_1 through FSI N. The first frequency section informationFSI_1 may include the memory polynomial modeling informationcorresponding to the first frequency section FS_1 and may include thefirst center frequency fc_1 of the first frequency section FS_1. Thememory polynomial modeling corresponding to the first frequency sectionFS_1 may include a first auto-correlation matrix ACM_1 and a firstcross-correlation vector CCV 1. In other words, the first frequencysection information FSI_1 may include the first auto-correlation matrixACM_1, the first cross-correlation vector CCV 1, and the first centerfrequency fc_1. A method of obtaining a memory polynomial modelinginformation corresponding to a given frequency band is described indetail with reference to the following drawings in conjunction withFIGS. 6 and 7.

FIG. 8 is a flowchart of a signal processing method of the device 10,according to an example embodiment of the inventive concept. FIG. 8 isdescribed with reference to FIG. 1.

The device 10 may determine a frequency section including at least aportion of a given frequency band among the plurality of frequencysections (S110). For example, the plurality of frequency sections may,as illustrated in FIG. 4, represent frequency sections that are dividedin the entire frequency band. In an embodiment, the device 10 maydetermine the frequency section including at least a portion of thegiven frequency band based on a start frequency and an end frequency ofthe given frequency band. For example, referring to FIG. 5 together,when the frequency band is given as illustrated in FIG. 5, the device 10may determine that the given frequency band spans over the thirdfrequency section FS_3 and the fourth frequency section FS_4.

The device 10 may obtain the auto-correlation matrix and thecross-correlation vector, based on the frequency section information FSIcorresponding to the determined at least one frequency section (S120).In other words, the device 10 may obtain the memory polynomial modelinginformation corresponding to the given frequency band, based on thefrequency section information FSI corresponding to the determined atleast one frequency section. For example, the parameter obtainingcircuit 300 in the device 10 may obtain the memory polynomial modelinginformation corresponding to the given frequency band, based on thememory polynomial modeling information corresponding to each of thedetermined at least one frequency section, the center frequencycorresponding to each of the determined at least one frequency section,and the center frequency fc of the given frequency band. For example, asdescribed in more detail below, the parameter obtaining circuit 300 mayobtain the auto-correlation matrix corresponding to the given frequencyband, based on the auto-correlation matrix corresponding to each of thedetermined at least one frequency section, the center frequencycorresponding to each of the determined at least one frequency section,and the center frequency fc of the given frequency band. Similarly, theparameter obtaining circuit 300 may obtain the cross-correlation vectorcorresponding to the given frequency band, based on thecross-correlation vector corresponding to each of the determined atleast one frequency section, the center frequency corresponding to eachof the determined at least one frequency section, and the centerfrequency fc of the given frequency band.

The device 10 may perform the pre-distortion based on the coefficientmatrix obtained based on the auto-correlation matrix and thecross-correlation vector that have been obtained in operation S120(S130). For example, the parameter obtaining circuit 300 may obtain thecoefficient matrix by performing a calculation of multiplying thecross-correlation vector corresponding to the given frequency band to aninverse matrix of the auto-correlation matrix corresponding to the givenfrequency band and may provide the obtained coefficient matrix to thepre-distortion circuit 100 as the parameter set PS. The pre-distortioncircuit 100 may, based on the parameter set PS, generate thepre-distorted signal PDS by performing the pre-distortion on the inputsignal IS.

FIG. 9 is a flowchart of a signal processing method according to anexample embodiment of the inventive concept. In particular, FIG. 9 is aflowchart of example detailed operations of operation S120 in FIG. 8.FIG. 9 is described below with reference to FIG. 1.

The device 10 may obtain the auto-correlation matrix corresponding tothe given frequency band, based on the center frequency fc of the givenfrequency band, the center frequency corresponding to the determined atleast one frequency section, and the auto-correlation matrixcorresponding to the determined at least one frequency section (S220).These operations (S220) may be performed by the parameter obtainingcircuit 300.

The device 10 may obtain the cross-correlation vector corresponding tothe given frequency band, based on the center frequency fc of the givenfrequency band, the center frequency corresponding to the determined atleast one frequency section, and the auto-correlation vectorcorresponding to the determined at least one frequency section (S240).These operations (S240) may be likewise performed by the parameterobtaining circuit 300.

FIG. 10 is a flowchart of a signal processing method according to anexample embodiment of the inventive concept. In particular, FIG. 10 is aflowchart of example detailed operations of operation S220 in FIG. 9.FIG. 10 is described with reference to FIG. 1.

To facilitate an understanding of the inventive concepts, FIG. 10illustrates a flowchart of a case where the determined at least onefrequency section includes the first frequency section FS_1 and thesecond frequency section FS_2, and the given frequency band spans thefirst and second frequency sections FS_1 and FS_2. Each of theoperations S322, S324, S342, S344 and S360 described below may beperformed by the parameter obtaining circuit 300 of the device 10.

The device 10 may obtain a first frequency shift vector, based on thecenter frequency fc corresponding to the given frequency band and thefirst center frequency fc_1, which is the center frequency of the firstfrequency section FS_1 (S322). In an embodiment, the first frequencyshift vector may be obtained by Formula 7 below. In Formula 7, FSV₁represents the first frequency shift vector, fc represents the centerfrequency of the given frequency band, fc₁ represents the first centerfrequency, T₁ represents a sampling time, and K represents a memorydepth.FSV₁ =ee(fc−fc ₁),ee(x)=[111e ^(2π×T) ¹ e ^(2π×T) ¹ e ^(2π×T) ¹ e ^(2π2×T) ¹ . . . e^(2π2×T) ¹ . . . e ^(2π(K−1)×T) ¹ ]^(T)  [Formula 7]

In Formula 7, ee (x) may function as an intermediate function, and whenQ is a nonlinear order, ee (x) may be a vector including K*Q elements.For example, ee (x) may represent a vector in which 1 is repeated for Qtimes, then e^(2π×T1) is repeated for Q times, then e^(2π2×T1) isrepeated for Q times, and finally, e^(2λ(K−1)×T1) is repeated for Qtimes.

The device 10 may obtain a first temporary auto-correlation matrix,based on the first frequency shift vector, and the firstauto-correlation matrix corresponding to the first frequency sectionFS_1 (S324). In an embodiment, the first temporary auto-correlationmatrix may be obtained by Formula 8 below. In Formula 8, TACM₁represents the first temporary auto-correlation matrix, ACM₁ representsthe first auto-correlation matrix, and FSV₁ represents the firstfrequency shift vector.TACM₁=ACM₁∘(FSV₁·FSV₁ ^(T))  [Formula 8]

In Formula 8, a matrix with T as a superscript denotes a transposedmatrix. In the calculation, ‘· denotes a matrix multiplication, and ‘∘’denotes the Hadamard product calculation. The Hadamard productcalculation may denote a multiplication calculation of elementscorresponding to the same position in two matrices to be multiplied andmay be referred to as an element-wise multiplication.

Similarly, the device 10 may obtain a second frequency shift vector,based on the center frequency fc corresponding to the given frequencyband and the second center frequency fc_2, which is the center frequencyof the second frequency section FS_2 (S342). In an embodiment, thesecond frequency shift vector may be obtained by Formula 9 below. InFormula 9, FSV₂ may represent the second frequency shift vector, fc mayrepresent the center frequency of the given frequency band, fc₂ mayrepresent the second center frequency, T₁ may represent the samplingtime, and K may represent the memory depth.ee(x)=[111e ^(2π×T) ¹ e ^(2π×T) ¹ e ^(2π×T) ¹ e ^(2π2×T) ¹ . . . e^(2π2×T) ¹ . . . e ^(2π(K−1)×T) ¹ ]^(T)  [Formula 9]

In Formula 9, ee (x) may function as an intermediate function, and whenQ is the nonlinear order, ee (x) may be the vector including K*Qelements. For example, ee (x) may represent a vector in which 1 isrepeated for Q times, then e^(2π×T1) is repeated for Q times, thene^(2π2×T1) is repeated for Q times, and finally, e^(2π(K−1)T1) isrepeated for Q times.

The device 10 may obtain a second temporary auto-correlation matrix,based on the second frequency shift vector and the secondauto-correlation matrix corresponding to the second frequency sectionFS_2 (S344). In an embodiment, the second temporary auto-correlationmatrix may be obtained by Formula 10 below. In Formula 10, TACM₂ mayrepresent the second temporary auto-correlation matrix, ACM₂ mayrepresent the second auto-correlation matrix, and FSV₂ may represent thesecond frequency shift vector.TACM₂=ACM₂∘(FSV₂·FSV₂ ^(T))  [Formula 10]

In Formula 10, a matrix with T as a superscript may denote a transposedmatrix. In the calculation, ‘·’ may denote a matrix multiplication, and‘∘’ may denote the Hadamard product calculation. The Hadamard productcalculation may denote a multiplication operation of elementscorresponding to the same position in two matrices to be multiplied andmay be referred to as an element-wise multiplication.

In other words, operation S320, which includes operations S322 and S324and is an operation of obtaining the first temporary auto-correlationmatrix, may be substantially similar to operation S340, which includesoperations S342 and S344 and is an operation of obtaining the secondtemporary auto-correlation matrix.

The device 10 may obtain the auto-correlation matrix corresponding tothe given frequency band based on the first temporary auto-correlationmatrix and the second temporary auto-correlation matrix (S360), e.g., bysumming the first and second temporary auto-correlation matrices. Theauto-correlation matrix corresponding to the given frequency band may beobtained by Formula 11 below, in which TACM₁ represents the firsttemporary auto-correlation matrix, TACM₂ represents the second temporaryauto-correlation matrix, ACM represents the auto-correlation matrixcorresponding to the given frequency band.ACM=TACM₁+TACM₂  [Formula 11]

FIG. 11 is a flowchart of a signal processing method according to anexample embodiment of the inventive concept. In particular, FIG. 11 maybe a flowchart of detailed operations of operation S220 in FIG. 9. FIG.11 is described below with reference to FIG. 1.

To facilitate an understanding of the inventive concept, FIG. 11illustrates a flowchart of a case where the determined at least onefrequency section includes the first frequency section FS_1, the secondfrequency section FS_2, and the third frequency section FS_3.

Operation S320 in FIG. 11 may be substantially the same as operationS320 in FIG. 10, and operation S340 in FIG. 11 may be substantially thesame as operation S340 in FIG. 10. In the description below, theoperations S352, S354 and S370 may be performed by the parameterobtaining circuit 300 of the device 10.

The device 10 may obtain a third frequency shift vector, based on thecenter frequency fc corresponding to the given frequency band and athird center frequency fc_3, which is the center frequency of the thirdfrequency section FS_3 (S352) A detailed method thereof may be similarto those of Formulas 7 and 9.

The device 10 may obtain a third temporary auto-correlation matrix,based on the third frequency shift vector and the third auto-correlationmatrix corresponding to the third frequency section FS_3 (S354). Adetailed method thereof may be similar to those of Formulas 8 and 10.

In other words, operation S350 including operations S352 and S354 may besubstantially similar to operations S320 and S340.

The device 10 may obtain the auto-correlation matrix corresponding tothe given frequency band based on the first temporary auto-correlationmatrix, the second temporary auto-correlation matrix, and the thirdtemporary auto-correlation matrix (S370), e.g., by summing the first,second and third temporary auto-correlation matrices. Theauto-correlation matrix corresponding to the given frequency band may beobtained by Formula 12 below, in which TACM₁, TACM₂, and TACM₃ representthe first, second and third temporary auto-correlation matrices,respectively, and ACM represents the auto-correlation matrixcorresponding to the given frequency band.ACM=TACM₁+TACM₂+TACM₃  [Formula 12]

An embodiment in which a given frequency band spans over two frequencysections is described with reference to FIG. 10, and an embodiment inwhich a given frequency band spans over three frequency sections isdescribed with reference to FIG. 11. In the case of an embodiment wherea given frequency band spans over four or more frequency sections, themethod of obtaining an auto-correlation matrix as described withreference to FIGS. 10 and 11 may be extrapolated analogously to obtainthe auto-correlation matrix using four or more temporaryauto-correlation matrices.

FIG. 12 is a flowchart of a signal processing method according to anexample embodiment of the inventive concept. In particular, FIG. 12 maybe a flowchart of detailed operations of operation S240 in FIG. 9. FIG.12 is described with reference to FIG. 1.

To facilitate an understanding of the inventive concept, FIG. 12illustrates a flowchart of a case where the determined at least onefrequency section includes the first frequency section FS_1 and thesecond frequency section FS_2. In the description below, the operationsS422, S424, S442, S444 and S460 may be performed by the parameterobtaining circuit 300 of the device 10.

The device 10 may obtain a first frequency shift vector, based on thecenter frequency fc corresponding to the given frequency band and thefirst center frequency fc_1, which is the center frequency of the firstfrequency section FS_1 (S422). In an embodiment, the first frequencyshift vector may be obtained by Formula 7 already described withreference to FIG. 10.

The device 10 may obtain the first temporary cross-correlation vector,based on the first frequency shift vector and the firstcross-correlation vector corresponding to the first frequency sectionFS_1 (S424). In an embodiment, the first cross-correlation vector may beobtained by Formula 13 below. In Formula 13, TCCV₁ represents the firsttemporary cross-correlation matrix, CCV₁ represents the firstcross-correlation matrix, and FSV₁ represents the first frequency shiftvector.TCCV₁=CCV₁∘(FSV₁·FSV₁ ^(T))  [Formula 13]

In Formula 13, a matrix with T as a superscript may denote a transposedmatrix. In the calculation, · “·’ may denote a matrix multiplication,and ∘ “∘’ may denote the Hadamard product calculation. The Hadamardproduct calculation may denote a multiplication calculation of elementscorresponding to the same position in two matrices to be multiplied andmay be referred to as an element-wise multiplication.

Similarly, the device 10 may obtain a second frequency shift vector,based on the center frequency fc corresponding to the given frequencyband and the second center frequency fc_2, which is the center frequencyof the second frequency section FS_2 (S442). In an embodiment, thesecond frequency shift vector may be obtained by Formula 9 alreadydescribed with reference to FIG. 10.

The device 10 may obtain the second temporary cross-correlation vector,based on the second frequency shift vector and the secondcross-correlation vector corresponding to the second frequency sectionFS_2 (S444). In an embodiment, the second cross-correlation vector maybe obtained by Formula 14 below. In Formula 14, TCCV₂ represents thesecond temporary cross-correlation matrix, CCV₂ represents the secondcross-correlation matrix, and FSV₂ represents the second frequency shiftvector.TCCV₂=CCV₂∘(FSV₂·FSV₂ ^(T))  [Formula 14]

In Formula 14, a matrix with T as a superscript denotes a transposedmatrix. In the calculation, “·” may denote a matrix multiplication, and“∘” may denote the Hadamard product calculation. The Hadamard productcalculation may denote a multiplication calculation of elementscorresponding to the same position in two matrices to be multiplied andmay be referred to as an element-wise multiplication.

In other words, operation S420, which includes operations S422 and S424and is an operation of obtaining the first temporary cross-correlationvector, may be substantially similar to operation S440, which includesoperations S442 and S444 and is an operation of obtaining the secondtemporary cross-correlation vector.

The device 10 may obtain the cross-correlation vector corresponding tothe given frequency band based on the first temporary cross-correlationvector and the second temporary cross-correlation vector (S460), e.g.,by summing the first and second temporary cross-correlation vectors. Thecross-correlation vector corresponding to the given frequency band maybe obtained by Formula 15 below. Here, TCCV₁ represents the firsttemporary cross-correlation vector, TCCV₂ represents the secondtemporary cross-correlation vector, and CCV represents thecross-correlation vector corresponding to the given frequency band.CCV=TCCV₁+TCCV₂  [Formula 15]

Referring to the descriptions given with reference to FIG. 12, a methodof obtaining a cross-correlation vector may be implemented in ananalogous, extrapolated manner as an embodiment in which a givenfrequency band spans over three or more frequency sections.

FIG. 13 is a diagram of the parameter obtaining circuit 300 according toan example embodiment of the inventive concept.

The parameter obtaining circuit 300 may include the auto-correlationmatrix obtaining circuit 310, the cross-correlation vector obtainingcircuit 320, and the coefficient matrix obtaining circuit 330.Descriptions of the auto-correlation matrix obtaining circuit 310, thecross-correlation vector obtaining circuit 320, and the coefficientmatrix obtaining circuit 330 are already given with respect to FIG. 6,and thus redundant description thereof is omitted.

The auto-correlation matrix obtaining circuit 310 may include a firstsection determination circuit 312, a first frequency shift vectorobtaining circuit 314, and an auto-correlation matrix calculationcircuit 316.

The first section determination circuit 312 may determine at least onefrequency section including at least a portion of the given frequencyband among the plurality of frequency sections. The first sectiondetermination circuit 312 may provide a determined section informationDS to the first frequency shift vector obtaining circuit 314.

The first frequency shift vector obtaining circuit 314 may, based on thedetermined section information DS, select frequency section informationFSI corresponding to at least one frequency section determined amongpieces of the frequency section information FSI, and may generate afrequency shift vector FSV based on the frequency section informationFSI corresponding to the determined at least one frequency section. Forexample, the first frequency shift vector obtaining circuit 314 maygenerate the frequency shift vector FSV according to Formula 7 describedwith respect to FIG. 10.

The auto-correlation matrix calculation circuit 316 may obtain theauto-correlation matrix ACM corresponding to a given frequency bandbased on the frequency shift vector FSV. For example, when the givenfrequency band spans over the first frequency section and the secondfrequency section, the auto-correlation matrix calculation circuit 316may, based on the frequency shift vector FSV, obtain theauto-correlation matrix ACM corresponding to the given frequency band byusing the same method as those in operations S324, S344, and S360 inFIG. 10.

The cross-correlation matrix obtaining circuit 320 may include a secondsection determination circuit 322, a second frequency shift vectorobtaining circuit 324, and a cross-correlation matrix calculationcircuit 326.

The second section determination circuit 322 may determine at least onefrequency section including at least a portion of the given frequencyband among the plurality of frequency sections. The second sectiondetermination circuit 322 may provide the determined section informationDS to the second frequency shift vector obtaining circuit 324.

The second frequency shift vector obtaining circuit 324 may, based onthe determined section information DS, select the frequency sectioninformation FSI corresponding to at least one frequency sectiondetermined among the frequency section information FSI, and may generatethe frequency shift vector FSV based on the frequency sectioninformation FSI corresponding to the determined at least one frequencysection. For example, the second frequency shift vector obtainingcircuit 324 may generate the frequency shift vector FSV according toFormula 7 described with respect to FIG. 10.

The cross-correlation matrix calculation circuit 326 may obtain thecross-correlation matrix ACM corresponding to the given frequency bandbased on the frequency shift vector FSV. For example, when the givenfrequency band spans over the first frequency section and the secondfrequency section, the cross-correlation matrix calculation circuit 326may, based on the frequency shift vector FSV, obtain thecross-correlation vector CCV corresponding to the given frequency bandby using the same method as those in operations S424, S444, and S460 inFIG. 12.

FIG. 14 is a diagram of the parameter obtaining circuit 300 according toan example embodiment of the inventive concept. In particular, FIG. 14illustrates another implementation of the parameter obtaining circuit300. FIG. 14 illustrates an embodiment in which a section determinationcircuit 340 and a frequency shift vector obtaining circuit 350 areshared as an implementation example of FIG. 13.

The parameter obtaining circuit 300 may include the auto-correlationmatrix obtaining circuit 310, the cross-correlation vector obtainingcircuit 320, the coefficient matrix obtaining circuit 330, the sectiondetermination circuit 340, and the frequency shift vector obtainingcircuit 350. Descriptions of the auto-correlation matrix obtainingcircuit 310, the cross-correlation vector obtaining circuit 320, and thecoefficient matrix obtaining circuit 330 already given with respect toFIG. 6 are omitted.

The section determination circuit 340 may have substantially the samefunction as the first section determination circuit 312 and the secondsection determination circuit 322 in FIG. 13. In other words, thesection determination circuit 340 may determine at least one frequencysection including at least a portion of the given frequency band amongthe plurality of frequency sections. The section determination circuit340 may provide the determined section information DS to the frequencyshift vector obtaining circuit 350.

The frequency shift vector obtaining circuit 350 may have asubstantially identical function to the first frequency shift vectorobtaining circuit 314 and the second frequency shift vector obtainingcircuit 324 in FIG. 13.

The auto-correlation matrix obtaining circuit 310 in FIG. 14 may have asubstantially identical function to the auto-correlation matrixcalculation circuit 316 in FIG. 13, and the cross-correlation vectorobtaining circuit 320 in FIG. 14 may have a substantially identicalfunction to the cross-correlation matrix calculation circuit 326 in FIG.13.

FIG. 15 illustrates the entire frequency band and the plurality offrequency sections (FS_1, FS_2, FS_3, FS_4, and FS_5), according to anexample embodiment of the inventive concept. Referring to FIG. 15,unlike FIG. 4, a frequency width of each of the plurality of frequencysections (FS_1, FS_2, FS_3, FS_4, and FS_5) may not be identical.

For example, a frequency width of a frequency section near the center ofthe entire frequency band may be less than those of frequency sectionsnear edges of the entire frequency band.

For example, frequency widths of the second frequency section FS_2, thethird frequency section FS_3, and the fourth frequency section FS_4 mayrepresent a first frequency width Δf1, and frequency widths of the firstfrequency section FS_1 and the fifth frequency section FS_5 near edgesof the entire frequency band may represent a second frequency width Δf2.In an embodiment, the first frequency width Δf1 may be less than thesecond frequency width Δf2.

FIG. 16 illustrates the entire frequency band and the plurality offrequency sections (FS_1, FS_2, FS_3, FS_4, and FS_5), according to anexample embodiment of the inventive concept. Referring to FIG. 16,unlike FIG. 4, frequency widths of the plurality of frequency sections(FS_1, FS_2, FS_3, FS_4, and FS_5) may not be identical to each other.

For example, the frequency width of the third frequency section FS_3 maybe the first frequency width Δf1, and the frequency widths of the secondfrequency section FS_2 and the fourth frequency section FS_4 may be thesecond frequency width Δf2, and the frequency widths of the firstfrequency section FS_1 and the fifth frequency section FS_5 may be thethird frequency width Δf3. The first frequency width Δf1 may be lessthan the second frequency width Δf2, and the second frequency width Δf2may be less than the third frequency width Δf3.

FIG. 17 illustrates a communication device 1000 according to an exampleembodiment of the inventive concept. As illustrated in FIG. 14, thecommunication device 1000 may include an application specific integratedcircuit (ASIC) 1100, an application specific instruction set processor(ASIP) 1300, a memory 1500, a main processor 1700, and a main memory1900. Two or more of the ASIC 1100, the ASIP 1300, and the mainprocessor 1700 may communicate with each other. In addition, at leasttwo or more of the ASIC 1100, the ASIP 1300, the memory 1500, the mainprocessor 1700, and the main memory 1900 may be embedded in one chip.

The ASIP 1300 may include an integrated circuit customized for aparticular usage, support a dedicated instruction set for a particularapplication, and execute instructions contained in the dedicatedinstruction set. The memory 1500 may communicate with the ASIP 1300, andmay store, as a non-volatile storage, a plurality of instructionsexecuted by the ASIP 1300. For example, the memory 1500 may include anarbitrary type memory accessible by the ASIP 1300, as a non-limitedexample, such as random access memory (RAM), read-only memory (ROM), atape, a magnetic disk, an optical disk, a volatile memory, anon-volatile memory, and a combination thereof.

The main processor 1700 may control the communication device 1000 byexecuting a plurality of instructions. For example, the main processor1700 may control the ASIC 1100 and the ASIP 1300, and process datareceived via the MIMO channel, or process a user input to thecommunication device 1000. The main memory 1900 may communicate with themain processor 1700, and may store, as a non-volatile storage, theplurality of instructions executed by main processor 1700. For example,the main memory 1900 may include an arbitrary type memory accessible bythe main processor 1700, as a non-limited example, such as RAM, ROM, atape, a magnetic disk, an optical disk, a volatile memory, anon-volatile memory, and a combination thereof.

An above-described method of compensating non-linearity of thetransmitter according to an example embodiment of the inventive conceptmay be performed by at least one of the components included in thecommunication device 1000 in FIG. 17. For example, the processor 500described above may be included in at least one of the ASIC 1100, theASIP 1300, the memory 1500, the main processor 1700, and the main memory1900 in FIG. 17. In some embodiments, at least one of the operations ofthe above-described method of compensating the non-linearity of thetransmitter 200 may be implemented as a plurality of instructions storedin memory 1500. In some embodiments, the ASIP 1300 may perform at leastone of the operations of the method of compensating the non-linearity ofthe transmitter 200 by executing the plurality of instructions stored inthe memory 1500. In some embodiments, at least one of the operations ofthe method of compensating the non-linearity of the transmitter 200 maybe implemented in a hardware block designed by using logic synthesis orthe like and be included in the ASIC 1100. In some embodiments, at leastone of the operations of the method compensating the non-linearity ofthe power amplifier 200 may be implemented as a plurality ofinstructions stored in the main memory 1900, and the main processor 1700may perform the at least one of the operations the method compensatingthe non-linearity of the power amplifier 200 by executing the pluralityof instructions stored in the main memory 1900.

While the inventive concept has been particularly shown and describedwith reference to embodiments thereof, it will be understood thatvarious changes in form and details may be made therein withoutdeparting from the spirit and scope of the following claims. Forinstance, while the inventive concept has been particularly shown anddescribed in connection with a wireless communication application, itmay be applied to correcting for nonlinearity in wired communicationsystems in other examples.

What is claimed is:
 1. A device configured to perform wirelesscommunication, the device comprising: a pre-distortion circuitconfigured to generate a pre-distorted signal by performingpre-distortion on an input signal based on a parameter set including aplurality of coefficients; a power amplifier configured to generate anoutput signal by amplifying a radio frequency (RF) signal based on thepre-distorted signal; and a parameter obtaining circuit configured toobtain, in the frequency domain, second memory polynomial modelinginformation corresponding to an operating frequency band based on firstmemory polynomial modeling information corresponding to each of aplurality of frequency sections of an entire frequency band over whichthe device is configured to operate, the parameter obtaining circuitbeing configured to obtain the parameter set according to an indirectlearning structure by using the second memory polynomial modelinginformation wherein at least one frequency section overlaps at least aportion of the operating frequency band among the plurality of frequencysections.
 2. The device of claim 1, wherein the parameter obtainingcircuit is configured to determine at least one frequency sectionoverlapping at least a portion of the operating frequency band among theplurality of frequency sections and obtain the second memory polynomialmodeling information based on the first memory polynomial modelinginformation corresponding to the determined at least one frequencysection.
 3. The device of claim 2, wherein each of the first memorypolynomial modeling information and the second memory polynomialmodeling information comprises: an auto-correlation matrix and across-correlation vector that are used for a matrix equation used forreducing a size of a difference between an intermediate signal based onthe output signal and the pre-distorted signal, according to anapplication of a Wiener filter.
 4. The device of claim 3, wherein theparameter obtaining circuit is configured to: generate at least onefrequency shift vector, based on a center frequency corresponding toeach of the determined at least one frequency section and a centerfrequency of the operating frequency band, and obtain theauto-correlation matrix corresponding to the operating frequency bandbased on the auto-correlation matrix corresponding to the determined atleast one frequency section and the at least one frequency shift vector.5. The device of claim 3, wherein the parameter obtaining circuit isconfigured to: when the determined at least one frequency sectioncomprises a first frequency section and a second frequency section,generate a first frequency shift vector based on a first centerfrequency corresponding to the first frequency section and a centerfrequency of the operating frequency band and obtain a first temporaryauto-correlation matrix, based on the first frequency shift vector and afirst auto-correlation matrix corresponding to the first frequencysection; generate a second frequency shift vector, based on a secondcenter frequency corresponding to the second frequency section and thecenter frequency of the operating frequency band; and obtain a secondtemporary auto-correlation matrix based on the second frequency shiftvector and a second auto-correlation matrix corresponding to the secondfrequency section; and obtain an auto-correlation matrix correspondingto the operating frequency band by performing a calculation of summingthe first temporary auto-correlation matrix and the second temporaryauto-correlation matrix.
 6. The device of claim 3, wherein the parameterobtaining circuit is configured to: generate at least one frequencyshift vector based on a center frequency corresponding to each of thedetermined at least one frequency section and a center frequency of theoperating frequency band, and obtain a cross-correlation vectorcorresponding to the operating frequency band based on across-correlation vector corresponding to the determined at least onefrequency section and the at least one frequency shift vector.
 7. Thedevice of claim 3, wherein the parameter obtaining circuit is configuredto: when the determined at least one frequency section comprises a firstfrequency section and a second frequency section, generate a firstfrequency shift vector based on a first center frequency correspondingto the first frequency section and a center frequency of the operatingfrequency band, and obtain a first temporary cross-correlation vector,based on the first frequency shift vector and a first cross-correlationvector corresponding to the first frequency section; generate a secondfrequency shift vector based on a second center frequency correspondingto the second frequency section and the center frequency of theoperating frequency band and obtain a second temporary cross-correlationvector, based on the second frequency shift vector and a secondcross-correlation vector corresponding to the second frequency section;and obtain a cross-correlation vector corresponding to the operatingfrequency band by performing a calculation of summing a first temporaryvector and the second temporary cross-correlation vector.
 8. The deviceof claim 1, further comprising a memory configured to store frequencysection information comprising a center frequency corresponding to thefirst memory polynomial modeling information and each of the pluralityof frequency sections.
 9. The device of claim 1, wherein the pluralityof sections each have an identical frequency width.
 10. The device ofclaim 1, wherein a frequency width of a center frequency section is lessthan that of an edge frequency section among the plurality of frequencysections, the center frequency section comprises a center frequency ofthe entire frequency band, and the edge frequency section comprises atleast one of a maximum frequency and a minimum frequency of the entirefrequency band.
 11. A method of processing a signal within a device, themethod comprising: determining at least one frequency section comprisingat least a portion of an operating frequency band of the device among aplurality of frequency sections that are divided from an entirefrequency band over which the device is configured to operate; obtainingan auto-correlation matrix corresponding to the operating frequency bandand a cross-correlation vector corresponding to the operating frequencyband, based on frequency section information corresponding to thedetermined at least one frequency section, the auto-correlation matrixand the cross-correlation vector being part of memory polynomialmodeling information that is obtained in the frequency domain based onthe frequency section information; and generating an output signal byperforming pre-distortion on an input signal by using a coefficientmatrix that is obtained based on the auto-correlation matrixcorresponding to the operating frequency band and the cross-correlationvector corresponding to the operating frequency band, wherein at leastone frequency section overlaps at least a portion of the operatingfrequency band among the plurality of frequency sections.
 12. The methodof claim 11, further comprising: determining the plurality of frequencysections by dividing the entire frequency band in identical intervals;and storing, in a memory in the device, a center frequency correspondingto each of the plurality of frequency sections, and an auto-correlationmatrix and a cross-correlation vector corresponding to each of theplurality of sections.
 13. The method of claim 11, further comprising:dividing a plurality of frequency sections such that a frequency widthof a frequency section near a center of the entire frequency band isless than a frequency width of a frequency section far from the centerof the entire frequency band; and storing, in a memory of the device, acenter frequency corresponding to each of the plurality of frequencysections, and an auto-correlation matrix and a cross-correlation vectorcorresponding to each of the plurality of frequency sections.
 14. Themethod of claim 11, wherein obtaining an auto-correlation matrixcorresponding to the operating frequency band and a cross-correlationvector corresponding to the operating frequency band further comprises:generating at least one frequency shift vector based on a centerfrequency corresponding to each of the determined at least one frequencysection and a center frequency of the operating frequency band; andobtaining an auto-correlation matrix corresponding to the operatingfrequency band based on the auto-correlation matrix corresponding to thedetermined at least one frequency section and the at least one frequencyshift vector.
 15. The method of claim 14, wherein the at least onefrequency section comprises a first frequency section and a secondfrequency section, wherein generating of the at least one frequencyshift vector based on a center frequency comprises: generating a firstfrequency shift vector based on a first center frequency correspondingto the first frequency section and a center frequency of the operatingfrequency band; and generating a second frequency shift vector based ona second center frequency corresponding to the second frequency sectionand a center frequency of the operating frequency band, wherein theobtaining of auto-correlation matrix corresponding to the operatingfrequency band comprises: obtaining a first temporary auto-correlationmatrix based on a first auto-correlation matrix corresponding to thefirst frequency shift vector and the first frequency section; obtaininga second temporary auto-correlation matrix based on the second frequencyshift vector and a second auto-correlation matrix corresponding to thesecond frequency section; and obtaining an auto-correlation matrixcorresponding to the operating frequency band by performing acalculation of summing the first temporary auto-correlation matrix andthe second temporary auto-correlation matrix.
 16. The method of claim15, wherein the obtaining of the first temporary auto-correlation matrixcomprises: performing a vector multiplication of the first frequencyshift vector by a transposed first frequency shift vector; and obtainingthe first temporary auto-correlation matrix by performing the Hadamardproduct calculation by using the first auto-correlation matrix and aresultant matrix of the vector multiplication.
 17. The method of claim11, wherein obtaining an auto-correlation matrix corresponding to theoperating frequency band and a cross-correlation vector corresponding tothe operating frequency band further comprises: generating at least onefrequency shift vector based on a center frequency corresponding to eachof the determined at least one frequency section and a center frequencyof the operating frequency band; and obtaining a cross-correlationvector corresponding to the operating frequency band based on thecross-correlation vector corresponding to the determined at least onefrequency section and the at least one frequency shift vector.
 18. Themethod of claim 17, wherein the at least one frequency section comprisesa first frequency section and a second frequency section, whereingenerating of the at least one frequency shift vector based on a centerfrequency comprises: generating a first frequency shift vector based ona first center frequency corresponding to the first frequency sectionand a center frequency of the operating frequency band; and generating asecond frequency shift vector based on a second center frequencycorresponding to the second frequency section and a center frequency ofthe operating frequency band, wherein the obtaining of across-correlation vector corresponding to the operating frequency bandcomprises: obtaining a first temporary cross-correlation vector based ona first cross-correlation vector corresponding to the first frequencyshift vector and the first frequency section; obtaining a secondtemporary cross-correlation vector based on a second cross-correlationvector corresponding to the second frequency shift vector and the secondfrequency section; and obtaining a cross-correlation vectorcorresponding to the operating frequency band by performing acalculation of summing the first temporary cross-correlation vector andthe second temporary cross-correlation vector.
 19. A device configuredto perform wireless communication, the device comprising: a memoryconfigured to store a plurality of pieces of frequency sectioninformation for a plurality of frequency sections and instructions foroperation of the device; a processor configured to performpre-distortion on an input signal in a given frequency band by executingat least one instruction among the instructions stored in the memory andgenerate the pre-distorted input signal; and a power amplifierconfigured to generate an output signal by amplifying the pre-distortedinput signal, wherein the processor is configured to determine at leastone frequency section comprising at least a portion of the givenfrequency band among the plurality of frequency sections and perform apre-distortion calculation on the input signal by using a coefficientmatrix obtained by using frequency section information corresponding tothe determined at least one frequency section among the plurality ofpieces of frequency section information, the coefficient matrix beingobtained based on polynomial information that is obtained in thefrequency domain based on the frequency section information, wherein atleast one frequency section overlaps at least a portion of the givenfrequency band among the plurality of frequency sections.
 20. The deviceof claim 19, wherein each of the plurality of pieces of frequencysection information comprises a center frequency corresponding to eachof the plurality of frequency sections, an auto-correlation matrix, anda cross-correlation vector.